from sklearn import svm
from sklearn.datasets import make_classification

X, y = make_classification(n_samples=100, n_features=2, n_redundant=0, random_state=42)

clf = svm.SVC(kernel='rbf', C=1.0, gamma='scale')
clf.fit(X, y)

print(clf.predict([[2.0, 3.0]]))
